Estimates of Sequences with Ultralong and Short CDR3s in the Bovine IgM B Cell Receptor Repertoire Using the Long-read Oxford Nanopore MinION Platform.

Cattle produce Abs with an H chain ultralong CDR3 (40-70 aa). These Abs have been shown to have features such as broad neutralization of viruses and are investigated as human therapeutics. A common issue in sequencing the bovine BCR repertoire is the sequence length required to capture variable (V) and isotype gene information. This study aimed to assess the use of Oxford Nanopore Technologies' MinION platform to perform IgM BCR repertoire sequencing to assess variation in the percentage of ultralong CDR3s among dairy cattle. Blood was collected from nine Holstein heifers. B cells were isolated using magnetic bead-based separation, RNA was extracted, and IgM+ transcripts were amplified using PCR and sequenced using a MinION R10.4 flow cell. The distribution of CDR3 lengths was trimodal, and the percentage of ultralong CDR3s ranged among animals from 2.32 to 20.13% in DNA sequences and 1.56% to 17.02% in productive protein sequences. V segment usage varied significantly among heifers. Segment IGHV1-7, associated with ultralong CDR3s, was used in 5.8-24.2% of sequences; usage was positively correlated with ultralong CDR3 production (r = 0.99, p < 0.01). To our knowledge, this is the first study to sequence the bovine BCR repertoire using Oxford Nanopore Technologies and demonstrates the potential for cost-efficient long-read repertoire sequencing in cattle without assembly. Findings from this study support literature describing the distribution of length and percentage of ultralong CDR3s. Future studies will investigate changes in the bovine BCR repertoire associated with age, antigenic exposure, and genetics.

The T-cell repertoire of Spanish patients with COVID-19 as a strategy to link T-cell characteristics to the severity of the disease.

BACKGROUND: The architecture and dynamics of T cell populations are critical in orchestrating the immune response to SARS-CoV-2. In our study, we used T Cell Receptor sequencing (TCRseq) to investigate TCR repertoires in 173 post-infection COVID-19 patients. METHODS: The cohort included 98 mild and 75 severe cases with a median age of 53. We amplified and sequenced the TCR ß chain Complementary Determining Region 3 (CDR3b) and performed bioinformatic analyses to assess repertoire diversity, clonality, and V/J allelic usage between age, sex and severity groups. CDR3b amino acid sequence inference was performed by clustering structural motifs and filtering validated reactive CDR3b to COVID-19. RESULTS: Our results revealed a pronounced decrease in diversity and an increase in clonal expansion in the TCR repertoires of severe COVID-19 patients younger than 55 years old. These results reflect the observed trends in patients older than 55 years old (both mild and severe). In addition, we identified a significant reduction in the usage of key V alleles (TRBV14, TRBV19, TRBV15 and TRBV6-4) associated with disease severity. Notably, severe patients under 55 years old had allelic patterns that resemble those over 55 years old, accompanied by a skewed frequency of COVID-19-related motifs. CONCLUSIONS: Present results suggest that severe patients younger than 55 may have a compromised TCR repertoire contributing to a worse disease outcome.

De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model.

Artificial Intelligence (AI) techniques have made great advances in assisting antibody design. However, antibody design still heavily relies on isolating antigen-specific antibodies from serum, which is a resource-intensive and time-consuming process. To address this issue, we propose a Pre-trained Antibody generative large Language Model (PALM-H3) for the de novo generation of artificial antibodies heavy chain complementarity-determining region 3 (CDRH3) with desired antigen-binding specificity, reducing the reliance on natural antibodies. We also build a high-precision model antigen-antibody binder (A2binder) that pairs antigen epitope sequences with antibody sequences to predict binding specificity and affinity. PALM-H3-generated antibodies exhibit binding ability to SARS-CoV-2 antigens, including the emerging XBB variant, as confirmed through in-silico analysis and in-vitro assays. The in-vitro assays validate that PALM-H3-generated antibodies achieve high binding affinity and potent neutralization capability against spike proteins of SARS-CoV-2 wild-type, Alpha, Delta, and the emerging XBB variant. Meanwhile, A2binder demonstrates exceptional predictive performance on binding specificity for various epitopes and variants. Furthermore, by incorporating the attention mechanism inherent in the Roformer architecture into the PALM-H3 model, we improve its interpretability, providing crucial insights into the fundamental principles of antibody design.

Chemical complementarity of tumor resident, T-cell receptor CDR3s and renalase-1 correlates with increased melanoma survival.

Overexpression of the secretory protein renalase-1 negatively impacts the survival of melanoma and pancreatic cancer patients, while inhibition of renalase-1 signaling drives tumor rejection by promoting T-cell activation. Thus, we investigated the chemical complementarity between melanoma-resident, T-cell receptor (TCR) complementarity-determining region 3 (CDR3) amino acid sequences (AAs) and the renalase-1 protein. Increasing complementarity of TCR CDR3s to renalase-1 AAs, as assessed by a chemical complementarity scoring algorithm, was associated with improved overall survival (OS) in melanoma patients. The expression levels of several immune signature genes were significantly, positively correlated with increasing TCR CDR3-renalase-1 complementarity scores. Additionally, the survival association observed with high complementarity of TCR CDR3s to renalase-1 AAs was more robust in cases with low renalase-1 gene expression levels. Mapping of TCR CDR3-renalase-1 in silico interaction sites identified major epitope candidates including RP220, the signaling module of the renalase-1 protein, consistent with the fact that a monoclonal antibody to RP220 is a potent inhibitor of melanoma growth. These findings indicate that renalase-1 is a potential antigen for TCR recognition in melanoma and could be considered as a target for immunotherapy.

Development of novel humanized VHH synthetic libraries based on physicochemical analyses.

Due to the high affinity and specificity of antibodies toward antigens, various antibody-based applications have been developed. Recently, variable antigen-binding domains of heavy-chain antibodies (VHH) have become an attractive alternative to conventional fragment antibodies due to their unique molecular characteristics. As an antibody-generating strategy, synthetic VHH libraries (including humanized VHH libraries) have been developed using distinct strategies to constrain the diversity of amino acid sequences. In this study, we designed and constructed several novel synthetic humanized VHH libraries based on biophysical analyses conducted using the complementarity determining region-grafting method and comprehensive sequence analyses of VHHs deposited in the protein data bank. We obtained VHHs from the libraries, and hit clones exhibited considerable thermal stability. We also found that VHHs from distinct libraries tended to have different epitopes. Based on our results, we propose a strategy for generating humanized VHHs with distinct epitopes toward various antigens by utilizing our library combinations.

Antibody-SGM, a Score-Based Generative Model for Antibody Heavy-Chain Design.

Traditional computational methods for antibody design involved random mutagenesis followed by energy function assessment for candidate selection. Recently, diffusion models have garnered considerable attention as cutting-edge generative models, lauded for their remarkable performance. However, these methods often focus solely on the backbone or sequence, resulting in the incomplete depiction of the overall structure and necessitating additional techniques to predict the missing component. This study presents Antibody-SGM, an innovative joint structure-sequence diffusion model that addresses the limitations of existing protein backbone generation models. Unlike previous models, Antibody-SGM successfully integrates sequence-specific attributes and functional properties into the generation process. Our methodology generates full-atom native-like antibody heavy chains by refining the generation to create valid pairs of sequences and structures, starting with random sequences and structural properties. The versatility of our method is demonstrated through various applications, including the design of full-atom antibodies, antigen-specific CDR design, antibody heavy chains optimization, validation with Alphafold3, and the identification of crucial antibody sequences and structural features. Antibody-SGM also optimizes protein function through active inpainting learning, allowing simultaneous sequence and structure optimization. These improvements demonstrate the promise of our strategy for protein engineering and significantly increase the power of protein design models.

Computational detection of antigen-specific B cell receptors following immunization.

B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and SARS-CoV-2 infections. We show that different lineages converge to the same responding Complementarity Determining Region 3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.

Worse Wilms' Tumor Outcomes Associated With Chemical Complementarity for Multiple T-Cell Receptor CDR3-CMV Epitope Pairs.

BACKGROUND/AIM: Wilms' tumors are pediatric renal tumors that generally have a good prognosis and outcomes. Viral illnesses have been linked to development of neoplasms and should be considered as a factor that could modulate overall survival. MATERIALS AND METHODS: We considered recently developed adaptive immune receptor, genomics and bioinformatics approaches to assess the potential impact of cytomegalovirus (CMV) infections in Wilms' tumor. RESULTS: T-cell receptor (TCR) complementarity determining region-3 (CDR3) amino acid sequences from Wilms' tumor specimens represented by the Therapeutically Applicable Research to Generate Effective Treatments dataset were compared with known anti-CMV TCR CDR3s, indicating that cases representing the anti-CMV TCR CDR3s had worse outcomes. Then, a chemical complementarity scoring approach for the Wilms' tumor, TCR CDR3s and a series of CMV antigens further indicated that cases representing a higher chemical complementarity to the CMV antigens had worse outcomes. CONCLUSION: Overall, we present a potentially novel method to assess CMV infections and identify patients who could benefit from therapies that address such infections.

Similar usage of T-cell receptor ß-chain between tumor and adjacent normal tissue in hepatocellular carcinoma.

BACKGROUND: In this study, we comprehensively profiled the T-cell receptor (TCR) repertoire of the tumor and adjacent normal tissue in patients with HBV-associated hepatocellular carcinoma (HCC) and determined the baseline characteristics and clinical significance of TCR. METHODS: High-throughput sequencing was used to determine the profile of complementarity-determining region 3 (CDR3) of the TCR-ß chain variable (TRBV) in the tumor and normal tissue samples of 14 HCC patients. At the same time, TRBV diversity and differences in expression between tumor and normal tissues were investigated. The cumulative frequency of top 100 CDR3 (CF100), clonality, and Shannon entropy as indices to evaluate diversity, RESULTS: The diversity of TRBV CDR3 showed no significant difference between tumor and normal tissues. Of the 58 V gene segments in TRBV, TRBV16 and TRBV7-6 had a significantly higher frequency in the tumor group than in the normal group (p < 0.05). The frequency of 14 J gene segments showed no significant difference between tumor and normal tissues. In contrast, the frequency of 22 TRBVx/BJx combinations was significantly higher in the tumor than in the normal tissue. In addition, the length and type of TRBV CDR3 were similar in tumor and normal tissues, and a Gaussian distribution was observed in both groups. CONCLUSION: This study provided a large amount of information about the TCR lineage in HBV-associated HCC, laying the foundation for further research. In addition, the fact that the immune repertoire (TRBV CDR3) hardly differs between tumor and adjacent normal tissue provides a new clue for exploring the mechanism of the liver as an organ with immune privileges.

Dysfunctional tumor-infiltrating Vδ1 + T lymphocytes in microsatellite-stable colorectal cancer.

Although γδ T cells are known to participate in immune dysregulation in solid tumors, their relevance to human microsatellite-stable (MSS) colorectal cancer (CRC) is still undefined. Here, using integrated gene expression analysis and T cell receptor sequencing, we characterized γδ T cells in MSS CRC, with a focus on Vδ1 + T cells. We identified Vδ1+ T cells with shared motifs in the third complementarity-determining region of the δ-chain, reflective of antigen recognition. Changes in gene and protein expression levels suggested a dysfunctional effector state of Vδ1+ T cells in MSS CRC, distinct from Vδ1+ T cells in microsatellite-instable (MSI). Interaction analysis highlighted an immunosuppressive role of fibroblasts in the dysregulation of Vδ1+ T cells in MSS CRC via the TIGIT-NECTIN2 axis. Blocking this pathway with a TIGIT antibody partially restored cytotoxicity of the dysfunctional Vδ1 phenotype. These results define an operative pathway in γδ T cells in MSS CRC.

The impact of exchanging the light and heavy chains on the structures of bovine ultralong antibodies.

The third complementary-determining regions of the heavy-chain (CDR3H) variable regions (VH) of some cattle antibodies are highly extended, consisting of 48 or more residues. These `ultralong' CDR3Hs form ß-ribbon stalks that protrude from the surface of the antibody with a disulfide cross-linked knob region at their apex that dominates antigen interactions over the other CDR loops. The structure of the Fab fragment of a naturally paired bovine ultralong antibody (D08), identified by single B-cell sequencing, has been determined to 1.6 Šresolution. By swapping the D08 native light chain with that of an unrelated antigen-unknown ultralong antibody, it is shown that interactions between the CDR3s of the variable domains potentially affect the fine positioning of the ultralong CDR3H; however, comparison with other crystallographic structures shows that crystalline packing is also a major contributor. It is concluded that, on balance, the exact positioning of ultralong CDR3H loops is most likely to be due to the constraints of crystal packing.

Humanization and characterization of an anti-ciguatoxin CTX3C monoclonal antibody.

Ciguatera poisoning (CP), caused by ciguatoxins (CTXs), is one of the most common food-borne diseases, affecting more than 50,000 people each year. In most cases, CP are managed with symptomatic and supportive remedies, and no specific treatment has been devised. In this study, toward the development of therapeutic antibodies for CP, we examined to humanize mouse anti-CTX3C antibody 10C9 (m10C9), which exhibited neutralizing activity against ciguatoxin in vitro and in vivo. The complementarity determining regions were grafted onto a human germline sequence with high sequence identity to m10C9, and the backmutations were examined to maintain the binding affinity. The optimized humanized antibody, Opt.h10C9Fab, showed a strong binding affinity to CTX3C with a high affinity (KD = 19.0 nM), and only two backmutations of ArgL46 and CysH94 in the framework regions were involved in determining the antigen binding affinity.

Allosteric nanobodies to study the interactions between SOS1 and RAS.

Protein-protein interactions (PPIs) are central in cell metabolism but research tools for the structural and functional characterization of these PPIs are often missing. Here we introduce broadly applicable immunization (Cross-link PPIs and immunize llamas, ChILL) and selection strategies (Display and co-selection, DisCO) for the discovery of diverse nanobodies that either stabilize or disrupt PPIs in a single experiment. We apply ChILL and DisCO to identify competitive, connective, or fully allosteric nanobodies that inhibit or facilitate the formation of the SOS1•RAS complex and modulate the nucleotide exchange rate on this pivotal GTPase in vitro as well as RAS signalling in cellulo. One of these connective nanobodies fills a cavity that was previously identified as the binding pocket for a series of therapeutic lead compounds. The long complementarity-determining region (CDR3) that penetrates this binding pocket serves as pharmacophore for extending the repertoire of potential leads.

Mechanistic Insights into How the Single Point Mutation Change the Autoantibody Repertoire.

A recent study showed that just one point mutation F33 to Y in the complementarity-determining region 1 of heavy chain (H-CDR1) could lead to the auto-antibody losing its DNA binding ability. However, the potential molecular mechanisms have not been well elucidated. In this study, we investigated how the antibody lost the DNA binding ability caused by mutation F33 to Y in the H-CDR1. We found that the electrostatic force was not the primary driving force for the interaction between anti-DNA antibodies and the antigen single strand DNA (ssDNA), and that the H-CDR2 largely contributed to the binding of antigen ssDNA, even larger than H-CDR1. The H-F33Y mutation could increase the hydrogen-bond interaction but impair the pi-pi stacking interaction between the antibody and ssDNA. We further found that F33H, W98H and Y95L in the wiletype antibody could form the stable pi-pi stacking interaction with the nucleotide bases of ssDNA. However, the Y33 in mutant could not form the parallel sandwich pi-pi stacking interaction with the ssDNA. To further confirm the importance of pi-pi stacking, the wildtype antibody and the mutants (F33YH, F33AH, W98AH and Y95AL) were experimentally expressed in CHO cells and purified, and the results from ELISA clearly showed that all the mutants lost the ssDNA binding ability. Taken together, our findings may not only deepen the understanding of the underlying interaction mechanism between autoantibody and antigen, but also broad implications in the field of antibody engineer.

B cells expressing mutated IGHV1-69-encoded antigen receptors related to virus neutralization show lymphoma-like transcriptomes in patients with chronic HCV infection.

BACKGROUND: Chronic HCV infection leads to a complex interplay with adaptive immune cells that may result in B cell dyscrasias like cryoglobulinemia or lymphoma. While direct-acting antiviral therapy has decreased the incidence of severe liver damage, its effect on extrahepatic HCV manifestations such as B cell dyscrasias is still unclear. METHODS: We sequenced B cell receptor (BCR) repertoires in patients with chronic HCV mono-infection and patients with HCV with a sustained virological response (SVR) after direct-acting antiviral therapy. This data set was mined for highly neutralizing HCV antibodies and compared to a diffuse large B cell lymphoma data set. The TKO model was used to test the signaling strength of selected B-BCRs in vitro. Single-cell RNA sequencing of chronic HCV and HCV SVR samples was performed to analyze the transcriptome of B cells with HCV-neutralizing antigen receptors. RESULTS: We identified a B cell fingerprint with high richness and somatic hypermutation in patients with chronic HCV and SVR. Convergence to specific immunoglobulin genes produced high-connectivity complementarity-determining region 3 networks. In addition, we observed that IGHV1-69 CDR1 and FR3 mutations characterizing highly neutralizing HCV antibodies corresponded to recurrent point mutations found in clonotypic BCRs of high-grade lymphomas. These BCRs did not show autonomous signaling but a lower activation threshold in an in vitro cell model for the assessment of BCR signaling strength. Single-cell RNA sequencing revealed that B cells carrying these point mutations showed a persisting oncogenic transcriptome signature with dysregulation in signaling nodes such as CARD11, MALT1, RelB, MAPK, and NFAT. CONCLUSIONS: We provide evidence that lymphoma-like cells derive from the anti-HCV immune response. In many patients, these cells persist for years after SVR and can be interpreted as a mechanistic basis for HCV-related B cell dyscrasias and increased lymphoma risk even beyond viral elimination.

Comparison of "framework Shuffling" and "CDR Grafting" in humanization of a PD-1 murine antibody.

Introduction: Humanization is typically adopted to reduce the immunogenicity of murine antibodies generated by hybridoma technology when used in humans. Methods: Two different strategies of antibody humanization are popularly employed, including "complementarity determining region (CDR) grafting" and "framework (FR) shuffling" to humanize a murine antibody against human programmed death-1 (PD-1), XM PD1. In CDR-grafting humanization, the CDRs of XM PD-1, were grafted into the human FR regions with high homology to the murine FR counterparts, and back mutations of key residues were performed to retain the antigen-binding affinities. While in FR-shuffling humanization, a combinatorial library of the six murine CDRs in-frame of XM PD-1 was constructed to a pool of human germline FRs for high-throughput screening for the most favorable variants. We evaluated many aspects which were important during antibody development of the molecules obtained by the two methods, including antibody purity, thermal stability, binding efficacy, predicted humanness, and immunogenicity, along with T cell epitope prediction for the humanized antibodies. Results: While the ideal molecule was not achieved through CDR grafting in this particular instance, FR-shuffling proved successful in identifying a suitable candidate. The study highlights FR-shuffling as an effective complementary approach that potentially increases the success rate of antibody humanization. It is particularly noted for its accessibility to those with a biological rather than a computational background. Discussion: The insights from this comparison are intended to assist other researchers in selecting appropriate humanization strategies for drug development, contributing to broader application and understanding in the field.

A single-domain antibody library based on a stability-engineered human VH3 scaffold.

Using conventional immunoglobulin G (IgG) molecules as therapeutic agents presents several well-known disadvantages owing to their large size and structural complexity, negatively impacting development and production efficiency. Single-domain antibodies (sdAbs) are the smallest functional antibody format (~ 15 kDa) and represent a viable alternative to IgG in many applications. However, unlike natural single-domain antibodies, such as camelid VHH, the variable domains of conventional antibodies show poor physicochemical properties when expressed as sdAbs. This report identified stable sdAb variants of human VH3-23 from a framework region 2-randomized human VH library by phage display selection under thermal challenge. Synthetic complementarity determining region diversity was introduced to one of the selected variants with high thermal stability, expression level, and monomeric content to construct a human VH sdAb library. The library was validated by panning against a panel of antigens, and target-specific binders were identified and characterized for their affinity and biophysical properties. The results of this study suggest that a synthetic sdAb library based on a stability-engineered human VH scaffold could be a facile source of high-quality sdAb for many practical applications.

Accurate prediction of CDR-H3 loop structures of antibodies with deep learning.

Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D structures of monoclonal antibodies and nanobodies. H3-OPT combines the strengths of AlphaFold2 with a pre-trained protein language model and provides a 2.24 Å average RMSDCα between predicted and experimentally determined CDR-H3 loops, thus outperforming other current computational methods in our non-redundant high-quality dataset. The model was validated by experimentally solving three structures of anti-VEGF nanobodies predicted by H3-OPT. We examined the potential applications of H3-OPT through analyzing antibody surface properties and antibody-antigen interactions. This structural prediction tool can be used to optimize antibody-antigen binding and engineer therapeutic antibodies with biophysical properties for specialized drug administration route.

IGH Complementarity Determining Region-3-Cytomegalovirus Protein Chemical Complementarity Linked to Better Overall Survival Probabilities for Glioblastoma.

Cytomegalovirus (CMV) has long been thought to have an association with glioblastoma multiforme (GBM), although the exact role of CMV and any subsequent implications for treatment have yet to be fully understood. This study addressed whether IGH complementarity determining region-3 (CDR3)-CMV protein chemical complementarity, with IGH CDR3s representing both tumor resident and blood-sourced IGH recombinations, was associated with overall survival (OS) distinctions. IGH recombination sequencing reads were obtained from (a) the Clinical Proteomic Tumor Analysis Consortium, tumor RNAseq files; and (b) the cancer genome atlas, blood exome-derived files. The Adaptive Match web tool was used to calculate chemical complementarity scores (CSs) based on hydrophobic interactions, and those scores were used to group GBM cases and assess survival probabilities. We found a higher OS probability for cases whose hydrophobic IGH CDR3-CMV protein chemical complementarity scores (Hydro CSs) were in the upper 50th percentile for several CMV proteins, including UL99 and UL123, as well as for CSs based on known B cell epitopes representing these proteins. We also identified multiple immune signature genes, including CD79A and TNFRSF17, for which higher RNA expression was associated with higher Hydro CSs. Results were consistent with the idea that stronger immunoglobulin responses to CMV are associated with better OS probabilities for GBM.

Protein loop structure prediction by community-based deep learning and its application to antibody CDR H3 loop modeling.

As of now, more than 60 years have passed since the first determination of protein structures through crystallography, and a significant portion of protein structures can be predicted by computers. This is due to the groundbreaking enhancement in protein structure prediction achieved through neural network training utilizing extensive sequence and structure data. However, substantial challenges persist in structure prediction due to limited data availability, with antibody structure prediction standing as one such challenge. In this paper, we propose a novel neural network architecture that effectively enables structure prediction by reflecting the inherent combinatorial nature involved in protein structure formation. The core idea of this neural network architecture is not solely to track and generate a single structure but rather to form a community of multiple structures and pursue accurate structure prediction by exchanging information among community members. Applying this concept to antibody CDR H3 loop structure prediction resulted in improved structure sampling. Such an approach could be applied in the structural and functional studies of proteins, particularly in exploring various physiological processes mediated by loops. Moreover, it holds potential in addressing various other types of combinatorial structure prediction and design problems.